BOL

shendurelab.github.io - LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly. Further information about LACHESIS, including source code, documentation and a user's guide are available...

Mapping reads to a reference genome is an essential step in many types of genomic analysis, such as variant calling and gene expression analysis.

If we only had Illumina reads, we could also assemble these using the tool Spades. You can try this here, or try it later on your own data. Get data We will use the same Illumina data as we used above: illumina_R1.fastq.gz: the Illumina...

bioinf.spbau.ru - SPAdes – St. Petersburg genome assembler – is intended for both standard isolates and single-cell MDA bacteria assemblies. This manual will help you to install and run SPAdes. SPAdes version 3.7.1 was released under GPLv2 on March 8,...

sourceforge.net - Contiguity preserving transposition and sequencing (CPT-seq) is an entirely in vitro means of generating libraries comprised of 9216 indexed pools, each of which contains thousands of sparsely sequenced long fragments ranging from 5 kilobases to...

When you have both Illumina and Nanopore data, then SPAdes remains a good option for hybrid assembly - SPAdes was used to produce the B fragilis assembly by Mick Watson’s group. Again, running spades.py will show you the...

github.com - Hagfish is a tool that is to be used in data analysis of Next Generation Sequencing (NGS) experiments. Hagfish builds on the concept of coverage plots and aims to assist (amongst others) in quality control of de novo genome assembly or...

Palindromes are sequences of nucleotides that read the same backward as forward.

biochem218.stanford.edu - Excellent article to introduce different sequencing methods along with tools for de novo assembly of sequencing reads and their relevant references. Title: Comparison of Short Read De Novo Alignment Algorithms  Author: Nikhil Gopal

github.com - Solutions to Coursera Genome Sequencing (Bioinformatics II)